Job Summary:

Job Description:

PayPal, Inc. seeks Staff Machine Learning Engineer in San Jose, CA

Job Duties: Lead the development and optimization of advanced machine learning (ML) models for implementation into existing software and systems using ML frameworks. Design, adapt, and integrate ML models into products and services, and deploy and maintain ML solutions in software production environments. Collaborate with other engineers, product management, and quality assurance analysts to ensure that the newly optimized software meets market needs concerning functionality, performance, availability, scalability, reliability, realistic implementation schedules, and adherence to software development goals and principles. Develop automated tests and deliver high-quality software code to production within a short development cycle in the continuous integration and delivery environment. Build cutting-edge testing technologies using next-generation automation techniques to resolve analytical software issues using programmatic solutions. Monitor and evaluate the performance of deployed models, making necessary adjustments using experience in cloud platforms and tools for data processing and model deployment. Partial telecommuting permitted from within a commutable distance.

Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Engineering, or a closely related field, plus four years of experience in the job offered or a related occupation.

Special Skill Requirements:

1. Experience in cloud computing & architecting data processing pipelines at scale using Spark, Hadoop/Hive, Cassandra, and AirFlow (4 years);

2. Experience in programming languages in Scala and Java (4 years)

3. Experience in Python programming languages (2 years)

4. Experience in deep learning architectures for user personalization systems at scale (4 years)

5. Experience in supervised and unsupervised ML modeling techniques for ranking and classification tasks (Gradient-Boosted Trees and regression models) (2 years)

6. Experience in TensorFlow or PyTorch (1 year)

7. Experience in Data-Driven Experimentation & A/B Testing (4 years)

8. Experience in Large Language Model fine-tuning for specific tasks (2 years)

9. Experience with LLM prompt optimization and output evaluation (2 years)

Additional Responsibilities & Preferred Qualifications:

The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is:

Primary Location | Pay Range:

San Jose, California | Salary: $227,639.00 - $300,500.00 per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.

Additional compensation for this role may include an annual performance bonus, equity, or other incentive compensation, as applicable.

Must be legally authorized to work in the U.S. without sponsorship.

Subsidiary:
PayPal

Travel Percent:
0

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. When making an application directly, we will never ask you to share passwords, one-time passcodes (OTP), or verification codes. Any such request is a red flag and likely part of a scam. All communication regarding your application will come from official PayPal email domains. If you suspect fraudulent activity, please report it immediately. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we're committed to building an equitable and inclusive global economy. And we can't do this without our most important asset-you. That's why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing-physical, emotional, and financial-delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.